Results 1  10
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14
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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to the correct marginals. However, on the QMR network, the loopy be liefs oscillated and had no obvious relation ship to the correct posteriors. We present some initial investigations into the cause of these oscillations, and show that some sim ple methods of preventing them lead to the wrong results
ANALYTICALLYSELECTED MULTIHYPOTHESIS INCREMENTAL MAP ESTIMATION
"... In this paper, we introduce an efficient maximum a posteriori (MAP) estimation algorithm, which effectively tracks multiple most probable hypotheses. In particular, due to multimodal distributions arising in most nonlinear problems, we employ a bank of MAP to track these modes (hypotheses). The ke ..."
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Cited by 1 (1 self)
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). The key idea is that we analytically determine all the posterior modes for the current state at each time step, which are used to generate highly probable hypotheses for the entire trajectory. Moreover, since it is expensive to solve the MAP problem sequentially over time by an iterative method
Preserving Modes and Messages via Diverse Particle Selection
"... In applications of graphical models arising in domains such as computer vision and signal processing, we often seek the most likely configurations of highdimensional, continuous variables. We develop a particlebased maxproduct algorithm which maintains a diverse set of posterior mode hypothe ..."
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Cited by 1 (0 self)
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In applications of graphical models arising in domains such as computer vision and signal processing, we often seek the most likely configurations of highdimensional, continuous variables. We develop a particlebased maxproduct algorithm which maintains a diverse set of posterior mode
The bayesian lasso
, 2005
"... The Lasso estimate for linear regression parameters can be interpreted as a Bayesian posterior mode estimate when the regression parameters have independent Laplace (doubleexponential) priors. Gibbs sampling from this posterior is possible using an expanded hierarchy with conjugate normal priors ..."
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Cited by 284 (0 self)
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The Lasso estimate for linear regression parameters can be interpreted as a Bayesian posterior mode estimate when the regression parameters have independent Laplace (doubleexponential) priors. Gibbs sampling from this posterior is possible using an expanded hierarchy with conjugate normal priors
Analysis of Bit Error Probability of DirectSequence CDMA Multiuser
"... We analyze the bit error probability of multiuser demodulators for directsequence binary phaseshiftkeying (DSIBPSK) CDMA channel with additive gaussian noise. The problem of multiuser demodulation is cast into the finitetemperature decoding problem, and replica analysis is applied to evaluate ..."
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the performance of the resulting MPM (Marginal Posterior Mode) demodulators, which include the optimal demodulator and the MAP demodulator as special cases. An approximate implementation of demodulators is proposed using analogvalued Hopfield model as a naive meanfield approximation to the MPM demodulators
P.: Particle filter based entropy
 In: 13th Conference on Information Fusion (FUSION
, 2010
"... Abstract – For many problems in the field of tracking or even the wider area of filtering the a posteriori description of the uncertainty can oftentimes not be described by a simple Gaussian density function. In such situations the characterization of the uncertainty by a mean and a covariance doe ..."
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Cited by 5 (3 self)
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does not capture the true extent of the uncertainty at hand. For example, when the posterior is multimodal with well separated narrow modes. Such descriptions naturally occur in applications like target tracking with terrain constraints or tracking of closely spaced multiple objects, where one cannot
Bag of textons for image segmentation via soft clustering and convex shift
 In Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR
, 2012
"... We propose an unsupervised image segmentation method based on texton similarity and mode seeking. The input image is first convolved with a filterbank, followed by soft clustering on its filter response to generate textons. The input image is then superpixelized where each belonging pixel is rega ..."
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Cited by 4 (0 self)
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is regarded as a voter and a soft voting histogram is constructed for each superpixel by averaging its voters ’ posterior texton probabilities. We further propose a modified mode seeking method called convex shift to group superpixels and generate segments. The distribution of superpixel histograms
Morphology of the human mitral valve. I. Chordae tendineae: a new classification. Circulation 41: 449–458
, 1970
"... Chordae tendineae from 50 normal mitral valves were studied. Four main types can be distinguished by their mode of insertion. Commissural chordae insert into and define the commissures between the anterior and posterior leaflets. Rough zone chordae insert into the ventricular aspect of the distal ro ..."
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Cited by 10 (0 self)
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rough portion of the anterior and posterior leaflets. Such rough zone chordae typically split into three cords before inserting into the leaflet. Two of the anterior leaflet rough zone chordae are thicker than the others and are called strut chordae. They insert at 4 and 8 o'clock positions
Computationally Efficient Estimation of Factor Multivariate Stochastic Volatility Models
, 2010
"... An Markov chain Monte Carlo simulation method based on a two stage delayed rejection MetropolisHastings algorithm is proposed to estimate a factor multivariate stochastic volatility model. The first stage uses ‘kstep iteration’ towards the mode, with k small, and the second stage uses an adaptive ..."
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more efficient than the approach of Chib, Nardari, and Shephard (2006). This increase in computational efficiency is particularly important in calculating marginal likelihoods because it is necessary to carry out the simulation a number of times to estimate the posterior ordinates for a given marginal
transcranial Doppler sonography. Correspondence
, 2012
"... Between 5 % and 37 % of patients are not suitable for transtemporal insonation with transcranial Doppler (TCD). This unsuitability is particularly frequent in elderly females and nonCaucasians. We aim to evaluate TCD efficiency in a mixed Hispanic population in Santiago, Chile and to determine whe ..."
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whether factors associated with the presence of optimal windows depend exclusively on patientrelated elements. Seven hundred fortynine patients were evaluated with power mode TCD. Optimal temporal windows (TWs) included detection of the middle, anterior, posterior cerebral arteries and terminal
Results 1  10
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14